CHS: Small: Scaffolding Data-Centered Interactions in Online Civic Discussions

该项目寻求提高新闻网站的循证讨论水平，方法是创建支持数据贡献的脚手架，并采用微任务工作流、激励和质量控制等众包概念。研究的愿景有两个方面：(1)帮助个人对公民问题形成更深的理解，使他们的贡献更有价值；(2)将这些贡献层回到原始新闻文章中，以便对于刚刚进入讨论的人来说，叙事和数据呈现不断改进。世界各地的社区都在努力应对住房、流动性和气候变化等公民问题。在线讨论系统为不同的受众提供了一个独特的机会，让他们共同围绕公民问题建立见解，但这些系统很少能发挥其潜力。最好的情况是，在线讨论给人们提供了一个发表意见的机会，但它们往往会成为传播谣言和错误信息的温床。大量的评论可能会让版主不知所措，很难突出能够推动社区发展的合理见解。这项研究旨在推进支撑以数据为中心的贡献的技术，以帮助社区围绕证据进行建设性的互动。这项研究将(1)通过分析过去十年来在三个热门新闻网站上的在线评论来表征以数据为中心的讨论的现状，(2)开发和比较基于数据素养教育的脚手架技术，以引导人们提供以数据为中心的观察、批评和改进，(3)进行对照实验，以评估这些支架如何影响个人成果，如理解和数据素养，讨论行为，如互惠，以及社区成果(包括两极分化)，以及(4)通过在以项目为基础的课堂上部署以气候变化为重点的新型在线讨论技术，并作为公民设计竞赛的一部分，开发和评估新颖的在线讨论技术。所有研究产品--包括数据集、分析方法和源代码--将提供给其他探索在线话语、数据科学、可视化和市政设计的研究人员。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This project seeks to increase the level of evidence-based discussion at news websites by creating scaffolding that supports data-literate contributions and by adopting concepts from crowdsourcing such as micro-task workflows, incentives, and quality control. The research vision is twofold: (1) to help individuals form a deeper understanding of a civic issue so that their contributions are more valuable, and (2) to layer these contributions back into the original news article so that the narrative and data presentation continually improve for people just entering the discussion. Communities everywhere grapple with civic issues, such as housing, mobility, and climate change. Online discussion systems offer a unique opportunity for diverse audiences to collaboratively build insights around a civic issue, but these systems rarely reach their potential. At best, online discussions give people a chance to express opinions, but all too often they become breeding grounds for trolling and misinformation. The volume of comments can overwhelm moderators, making it difficult to highlight well-reasoned insights that can advance a community. This research aims to advance technologies that scaffold data-centered contributions in order to help communities interact constructively around evidence. The research will (1) characterize the current state of data-centered discussion by analyzing the past ten years of online commenting on three popular news websites, (2) develop and compare scaffolding techniques based on data literacy education that would orient people to offer data-centered observations, critiques, and improvements, (3) conduct controlled experiments to evaluate how these scaffolds affect personal outcomes like comprehension and data literacy, discussion behavior such as reciprocity, and community outcomes including polarization, and (4) develop and evaluate novel online discussion technology through real-world deployments in a project-based classroom focused on climate change and as part of a civic design competition. All research products - including data sets, analysis methods, and source code - will be made available to other researchers exploring online discourse, data science, visualization, and civic design.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.